Paper recorded by Signals 4 on 2026-09-22 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-22 on arXiv · recorded by Signals 4 on 2026-09-23
Category: cs.LG · 机器学习 · first seen 2026-09-23
Offline reinforcement learning and off-policy evaluation evaluates dynamic treatment rules based on retrospectively collected data prior to deployment. In recent AI applications, state and reward information is recorded as complex text or image, which recent AI advancements such as LLM-as-a-judge can label with unknown bias. Expert annotation may be available but at a higher cost. For example, saf